Based on prior knowledge, the feature DIQ010, which indicates if the respondent is diabetic, can be used to predict whether the person is a senior or not. However, further analysis is needed to determine the appropriate ranges of values for each age group.

To conduct this analysis, we can start by grouping the data into the two target classes: 'Adult' and 'Senior'. Then, we can calculate the typical values of feature DIQ010 for each target class.

Here is the generated dictionary:

```json
{
	"Adult": [0.0, 1.0, 2.0, 3.0, 7.0],
	"Senior": [0.0, 1.0, 2.0, 3.0, 7.0]
}
```

Please note that the values [0.0, 1.0, 2.0, 3.0, 7.0] are placeholders and may not reflect the actual typical values for each target class. This analysis is based on the assumption that the range of values for DIQ010 can have different meanings for different age groups. It is essential to have a more comprehensive understanding of the data and domain knowledge to accurately determine the appropriate ranges of values for each target class.